FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2017
Deprecated data
Latest version(s):
u5vEk_IGFQ28RSZiwYLHUm-Q
11676/3uLIBns-hayfkUmwqvXDOyt2 (link)
X-BASE ET_T (Transpiration) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).
2017-01-01 12:00:00
2017-12-01 12:00:00
monthly
Gans, F., Duveiller, G., Hamdi, Z., Jung, M., Kraft, B., Nelson, J., Walther, S., Weber, U., Zhang, W. (2023). FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2017, Miscellaneous, https://hdl.handle.net/11676/3uLIBns-hayfkUmwqvXDOyt2
BibTex
@misc{https://hdl.handle.net/11676/3uLIBns-hayfkUmwqvXDOyt2, author={Gans, Fabian and Duveiller, Gregory and Hamdi, Zayd and Jung, Martin and Kraft, Basil and Nelson, Jacob A. and Walther, Sophia and Weber, Ulrich and Zhang, Weijie}, title={FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2017}, year={2023}, note={X-BASE ET_T (Transpiration) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA).}, keywords={BIOGEOCHEMICAL CYCLES, ECOSYSTEM FUNCTIONS, TERRESTRIAL ECOSYSTEMS, VEGETATION, CARBON, LAND SURFACE, FLUXCOM}, url={https://hdl.handle.net/11676/3uLIBns-hayfkUmwqvXDOyt2}, publisher={Carbon Portal}, copyright={http://meta.icos-cp.eu/ontologies/cpmeta/icosLicence}, pid={11676/3uLIBns-hayfkUmwqvXDOyt2} }
RIS
TY - DATA T1 - FLUXCOM-X monthly transpiration on global 0.5 degree grid for 2017 ID - 11676/3uLIBns-hayfkUmwqvXDOyt2 PY - 2023 AB - X-BASE ET_T (Transpiration) is based on the FLUXCOM-X framework which trains machine learning models on in-situ eddy covariance data and uses them to produce this global product. The X-BASE experiment is a basic configuration to serve as a baseline for the FLUXCOM-X framework and includes as predictors the core meteorlogical data, plant functional type classification as well as MODIS based vegitation indicies and land surface temperature. XGBoost was used as the machine learning algorithm. The transpiration estimates from the eddy covariance data was based on the Transpiration Estimation Algorithm (TEA). UR - https://hdl.handle.net/11676/3uLIBns-hayfkUmwqvXDOyt2 PB - Carbon Portal AU - Gans, Fabian AU - Duveiller, Gregory AU - Hamdi, Zayd AU - Jung, Martin AU - Kraft, Basil AU - Nelson, Jacob A. AU - Walther, Sophia AU - Weber, Ulrich AU - Zhang, Weijie KW - BIOGEOCHEMICAL CYCLES KW - ECOSYSTEM FUNCTIONS KW - TERRESTRIAL ECOSYSTEMS KW - VEGETATION KW - CARBON KW - LAND SURFACE KW - FLUXCOM ER -
ET_T_2017_monthly_halfdeg.nc
5 MB (5014954 bytes)
3
Production
2023-06-21 00:00:00
Gregory Duveiller,
Zayd Hamdi,
Martin Jung,
Basil Kraft,
Jacob A. Nelson,
Sophia Walther,
Ulrich Weber,
Weijie Zhang
Previewable variables
Name | Value type | Unit | Quantity kind | Preview |
---|---|---|---|---|
ET_T | transpiration | mm h-1 | particle flux | Preview |
Statistics
0
0
Technical information
dee2c8067b3e85ac9f9149b0aaf5c33b2b765e3696f8cc8d7e89e4adcb60d9b4
3uLIBns+hayfkUmwqvXDOyt2XjaW+MyNfonkrctg2bQ
S: -90, W: -180, N: 90, E: 180
BIOGEOCHEMICAL CYCLES
CARBON
ECOSYSTEM FUNCTIONS
FLUXCOM
LAND SURFACE
TERRESTRIAL ECOSYSTEMS
VEGETATION
biosphere modeling
carbon flux